{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-title"
    ]
   },
   "source": [
    "# Multiclass Support Vector Machine exercise\n",
    "\n",
    "*Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more details see the [assignments page](http://vision.stanford.edu/teaching/cs231n/assignments.html) on the course website.*\n",
    "\n",
    "In this exercise you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [],
   "source": [
    "# Run some setup code for this notebook.\n",
    "import random\n",
    "import numpy as np\n",
    "from cs231n.data_utils import load_CIFAR10\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# This is a bit of magic to make matplotlib figures appear inline in the\n",
    "# notebook rather than in a new window.\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# Some more magic so that the notebook will reload external python modules;\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "## CIFAR-10 Data Loading and Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (50000, 32, 32, 3)\n",
      "Training labels shape:  (50000,)\n",
      "Test data shape:  (10000, 32, 32, 3)\n",
      "Test labels shape:  (10000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the raw CIFAR-10 data.\n",
    "cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "\n",
    "# Cleaning up variables to prevent loading data multiple times (which may cause memory issue)\n",
    "try:\n",
    "   del X_train, y_train\n",
    "   del X_test, y_test\n",
    "   print('Clear previously loaded data.')\n",
    "except:\n",
    "   pass\n",
    "\n",
    "X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "\n",
    "# As a sanity check, we print out the size of the training and test data.\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Training labels shape: ', y_train.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 70 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize some examples from the dataset.\n",
    "# We show a few examples of training images from each class.\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "num_classes = len(classes)\n",
    "samples_per_class = 7\n",
    "for y, cls in enumerate(classes):\n",
    "    idxs = np.flatnonzero(y_train == y)\n",
    "    idxs = np.random.choice(idxs, samples_per_class, replace=False)\n",
    "    for i, idx in enumerate(idxs):\n",
    "        plt_idx = i * num_classes + y + 1\n",
    "        plt.subplot(samples_per_class, num_classes, plt_idx)\n",
    "        plt.imshow(X_train[idx].astype('uint8'))\n",
    "        plt.axis('off')\n",
    "        if i == 0:\n",
    "            plt.title(cls)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 32, 32, 3)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 32, 32, 3)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 32, 32, 3)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Split the data into train, val, and test sets. In addition we will\n",
    "# create a small development set as a subset of the training data;\n",
    "# we can use this for development so our code runs faster.\n",
    "num_training = 49000\n",
    "num_validation = 1000\n",
    "num_test = 1000\n",
    "num_dev = 500\n",
    "\n",
    "# Our validation set will be num_validation points from the original\n",
    "# training set.\n",
    "mask = range(num_training, num_training + num_validation)\n",
    "X_val = X_train[mask]\n",
    "y_val = y_train[mask]\n",
    "\n",
    "# Our training set will be the first num_train points from the original\n",
    "# training set.\n",
    "mask = range(num_training)\n",
    "X_train = X_train[mask]\n",
    "y_train = y_train[mask]\n",
    "\n",
    "# We will also make a development set, which is a small subset of\n",
    "# the training set.\n",
    "mask = np.random.choice(num_training, num_dev, replace=False)\n",
    "X_dev = X_train[mask]\n",
    "y_dev = y_train[mask]\n",
    "\n",
    "# We use the first num_test points of the original test set as our\n",
    "# test set.\n",
    "mask = range(num_test)\n",
    "X_test = X_test[mask]\n",
    "y_test = y_test[mask]\n",
    "\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (49000, 3072)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Test data shape:  (1000, 3072)\n",
      "dev data shape:  (500, 3072)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: reshape the image data into rows\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], -1))\n",
    "X_val = np.reshape(X_val, (X_val.shape[0], -1))\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], -1))\n",
    "X_dev = np.reshape(X_dev, (X_dev.shape[0], -1))\n",
    "\n",
    "# As a sanity check, print out the shapes of the data\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('dev data shape: ', X_dev.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[130.64189796 135.98173469 132.47391837 130.05569388 135.34804082\n",
      " 131.75402041 130.96055102 136.14328571 132.47636735 131.48467347]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49000, 3073) (1000, 3073) (1000, 3073) (500, 3073)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: subtract the mean image\n",
    "# first: compute the image mean based on the training data\n",
    "mean_image = np.mean(X_train, axis=0)\n",
    "print(mean_image[:10]) # print a few of the elements\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.imshow(mean_image.reshape((32,32,3)).astype('uint8')) # visualize the mean image\n",
    "plt.show()\n",
    "\n",
    "# second: subtract the mean image from train and test data\n",
    "X_train -= mean_image\n",
    "X_val -= mean_image\n",
    "X_test -= mean_image\n",
    "X_dev -= mean_image\n",
    "\n",
    "# third: append the bias dimension of ones (i.e. bias trick) so that our SVM\n",
    "# only has to worry about optimizing a single weight matrix W.\n",
    "X_train = np.hstack([X_train, np.ones((X_train.shape[0], 1))])\n",
    "X_val = np.hstack([X_val, np.ones((X_val.shape[0], 1))])\n",
    "X_test = np.hstack([X_test, np.ones((X_test.shape[0], 1))])\n",
    "X_dev = np.hstack([X_dev, np.ones((X_dev.shape[0], 1))])\n",
    "\n",
    "print(X_train.shape, X_val.shape, X_test.shape, X_dev.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVM Classifier\n",
    "\n",
    "Your code for this section will all be written inside `cs231n/classifiers/linear_svm.py`. \n",
    "\n",
    "As you can see, we have prefilled the function `svm_loss_naive` which uses for loops to evaluate the multiclass SVM loss function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 9.266702\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the naive implementation of the loss we provided for you:\n",
    "from cs231n.classifiers.linear_svm import svm_loss_naive\n",
    "import time\n",
    "\n",
    "# generate a random SVM weight matrix of small numbers\n",
    "W = np.random.randn(3073, 10) * 0.0001 \n",
    "\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `grad` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have correctly implemented the gradient correctly, you can numerically estimate the gradient of the loss function and compare the numeric estimate to the gradient that you computed. We have provided code that does this for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: -29.066030 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -12.978796 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -25.190907 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -40.592401 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -50.653379 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -3.141147 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -12.136374 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -43.977116 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: -9.402384 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: 7.911772 analytic: 0.000000, relative error: 1.000000e+00\n",
      "numerical: 20.076062 analytic: -0.004254, relative error: 1.000000e+00\n",
      "numerical: -3.366565 analytic: -0.002235, relative error: 9.986731e-01\n",
      "numerical: 6.688476 analytic: 0.002044, relative error: 9.993889e-01\n",
      "numerical: 5.342561 analytic: -0.000981, relative error: 1.000000e+00\n",
      "numerical: -4.447587 analytic: -0.002607, relative error: 9.988286e-01\n",
      "numerical: -18.229143 analytic: -0.006036, relative error: 9.993380e-01\n",
      "numerical: 2.591338 analytic: -0.010334, relative error: 1.000000e+00\n",
      "numerical: 15.855347 analytic: 0.007850, relative error: 9.990103e-01\n",
      "numerical: 16.970549 analytic: 0.000029, relative error: 9.999965e-01\n",
      "numerical: 26.186406 analytic: -0.001355, relative error: 1.000000e+00\n"
     ]
    }
   ],
   "source": [
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should match\n",
    "# almost exactly along all dimensions.\n",
    "from cs231n.gradient_check import grad_check_sparse\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 0.0)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)\n",
    "\n",
    "# do the gradient check once again with regularization turned on\n",
    "# you didn't forget the regularization gradient did you?\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 5e1)\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 5e1)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline Question 1**\n",
    "\n",
    "It is possible that once in a while a dimension in the gradcheck will not match exactly. What could such a discrepancy be caused by? Is it a reason for concern? What is a simple example in one dimension where a gradient check could fail? How would change the margin affect of the frequency of this happening? *Hint: the SVM loss function is not strictly speaking differentiable*\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ *fill this in.*  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "vectorized_time_1",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 9.266702e+00 computed in 0.035841s\n",
      "Vectorized loss: 9.266702e+00 computed in 0.006473s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Next implement the function svm_loss_vectorized; for now only compute the loss;\n",
    "# we will implement the gradient in a moment.\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss: %e computed in %fs' % (loss_naive, toc - tic))\n",
    "\n",
    "from cs231n.classifiers.linear_svm import svm_loss_vectorized\n",
    "tic = time.time()\n",
    "loss_vectorized, _ = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss: %e computed in %fs' % (loss_vectorized, toc - tic))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('difference: %f' % (loss_naive - loss_vectorized))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "vectorized_time_2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss and gradient: computed in 0.055150s\n",
      "Vectorized loss and gradient: computed in 0.006522s\n",
      "difference: 3240.329882\n"
     ]
    }
   ],
   "source": [
    "# Complete the implementation of svm_loss_vectorized, and compute the gradient\n",
    "# of the loss function in a vectorized way.\n",
    "\n",
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "tic = time.time()\n",
    "_, grad_vectorized = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a matrix, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "difference = np.linalg.norm(grad_naive - grad_vectorized, ord='fro')\n",
    "print('difference: %f' % difference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stochastic Gradient Descent\n",
    "\n",
    "We now have vectorized and efficient expressions for the loss, the gradient and our gradient matches the numerical gradient. We are therefore ready to do SGD to minimize the loss. Your code for this part will be written inside `cs231n/classifiers/linear_classifier.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "sgd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 793.321652\n",
      "iteration 100 / 1500: loss 474.189026\n",
      "iteration 200 / 1500: loss 287.558977\n",
      "iteration 300 / 1500: loss 175.926846\n",
      "iteration 400 / 1500: loss 107.922715\n",
      "iteration 500 / 1500: loss 67.209744\n",
      "iteration 600 / 1500: loss 42.896154\n",
      "iteration 700 / 1500: loss 27.752408\n",
      "iteration 800 / 1500: loss 19.114171\n",
      "iteration 900 / 1500: loss 13.265673\n",
      "iteration 1000 / 1500: loss 10.327546\n",
      "iteration 1100 / 1500: loss 8.215708\n",
      "iteration 1200 / 1500: loss 7.783702\n",
      "iteration 1300 / 1500: loss 6.735324\n",
      "iteration 1400 / 1500: loss 5.887126\n",
      "That took 7.540345s\n"
     ]
    }
   ],
   "source": [
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "tic = time.time()\n",
    "loss_hist = svm.train(X_train, y_train, learning_rate=1e-7, reg=2.5e4,\n",
    "                      num_iters=1500, verbose=True)\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A useful debugging strategy is to plot the loss as a function of\n",
    "# iteration number:\n",
    "plt.plot(loss_hist)\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "validate"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 0.378510\n",
      "validation accuracy: 0.379000\n"
     ]
    }
   ],
   "source": [
    "# Write the LinearSVM.predict function and evaluate the performance on both the\n",
    "# training and validation set\n",
    "y_train_pred = svm.predict(X_train)\n",
    "print('training accuracy: %f' % (np.mean(y_train == y_train_pred), ))\n",
    "y_val_pred = svm.predict(X_val)\n",
    "print('validation accuracy: %f' % (np.mean(y_val == y_val_pred), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "tuning",
    "tags": [
     "code"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 803.331827\n",
      "iteration 100 / 1500: loss 473.985776\n",
      "iteration 200 / 1500: loss 286.717911\n",
      "iteration 300 / 1500: loss 175.167755\n",
      "iteration 400 / 1500: loss 107.169357\n",
      "iteration 500 / 1500: loss 66.931128\n",
      "iteration 600 / 1500: loss 42.566611\n",
      "iteration 700 / 1500: loss 28.298821\n",
      "iteration 800 / 1500: loss 19.627054\n",
      "iteration 900 / 1500: loss 12.833125\n",
      "iteration 1000 / 1500: loss 10.338200\n",
      "iteration 1100 / 1500: loss 8.812515\n",
      "iteration 1200 / 1500: loss 7.278214\n",
      "iteration 1300 / 1500: loss 5.967952\n",
      "iteration 1400 / 1500: loss 5.924765\n",
      "iteration 0 / 1500: loss 326.812456\n",
      "iteration 100 / 1500: loss 259.942396\n",
      "iteration 200 / 1500: loss 211.898093\n",
      "iteration 300 / 1500: loss 173.231992\n",
      "iteration 400 / 1500: loss 141.796668\n",
      "iteration 500 / 1500: loss 117.091897\n",
      "iteration 600 / 1500: loss 95.304693\n",
      "iteration 700 / 1500: loss 79.500039\n",
      "iteration 800 / 1500: loss 65.609145\n",
      "iteration 900 / 1500: loss 54.377160\n",
      "iteration 1000 / 1500: loss 44.602233\n",
      "iteration 1100 / 1500: loss 38.391244\n",
      "iteration 1200 / 1500: loss 31.515326\n",
      "iteration 1300 / 1500: loss 26.431621\n",
      "iteration 1400 / 1500: loss 23.048453\n",
      "iteration 0 / 1500: loss 942.380611\n",
      "iteration 100 / 1500: loss 512.104337\n",
      "iteration 200 / 1500: loss 281.016302\n",
      "iteration 300 / 1500: loss 155.244619\n",
      "iteration 400 / 1500: loss 86.716720\n",
      "iteration 500 / 1500: loss 49.949535\n",
      "iteration 600 / 1500: loss 29.816328\n",
      "iteration 700 / 1500: loss 18.653129\n",
      "iteration 800 / 1500: loss 13.308972\n",
      "iteration 900 / 1500: loss 10.073171\n",
      "iteration 1000 / 1500: loss 7.353731\n",
      "iteration 1100 / 1500: loss 6.220979\n",
      "iteration 1200 / 1500: loss 6.065464\n",
      "iteration 1300 / 1500: loss 5.668547\n",
      "iteration 1400 / 1500: loss 5.721910\n",
      "iteration 0 / 1500: loss 635.311842\n",
      "iteration 100 / 1500: loss 418.059240\n",
      "iteration 200 / 1500: loss 279.117604\n",
      "iteration 300 / 1500: loss 187.970280\n",
      "iteration 400 / 1500: loss 126.760377\n",
      "iteration 500 / 1500: loss 86.467143\n",
      "iteration 600 / 1500: loss 59.833884\n",
      "iteration 700 / 1500: loss 41.063943\n",
      "iteration 800 / 1500: loss 29.419052\n",
      "iteration 900 / 1500: loss 21.120979\n",
      "iteration 1000 / 1500: loss 16.595698\n",
      "iteration 1100 / 1500: loss 11.831724\n",
      "iteration 1200 / 1500: loss 9.751589\n",
      "iteration 1300 / 1500: loss 8.817307\n",
      "iteration 1400 / 1500: loss 7.124062\n",
      "iteration 0 / 1500: loss 788.150708\n",
      "iteration 100 / 1500: loss 174.006785\n",
      "iteration 200 / 1500: loss 42.107182\n",
      "iteration 300 / 1500: loss 13.904484\n",
      "iteration 400 / 1500: loss 7.538207\n",
      "iteration 500 / 1500: loss 5.558741\n",
      "iteration 600 / 1500: loss 5.493569\n",
      "iteration 700 / 1500: loss 5.660461\n",
      "iteration 800 / 1500: loss 5.755526\n",
      "iteration 900 / 1500: loss 5.245239\n",
      "iteration 1000 / 1500: loss 5.432242\n",
      "iteration 1100 / 1500: loss 5.523228\n",
      "iteration 1200 / 1500: loss 5.788269\n",
      "iteration 1300 / 1500: loss 5.736710\n",
      "iteration 1400 / 1500: loss 5.661883\n",
      "iteration 0 / 1500: loss 325.200022\n",
      "iteration 100 / 1500: loss 171.802778\n",
      "iteration 200 / 1500: loss 95.009897\n",
      "iteration 300 / 1500: loss 54.088458\n",
      "iteration 400 / 1500: loss 31.308886\n",
      "iteration 500 / 1500: loss 19.205449\n",
      "iteration 600 / 1500: loss 12.723689\n",
      "iteration 700 / 1500: loss 9.189079\n",
      "iteration 800 / 1500: loss 7.505324\n",
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "lr 1.000000e-07 reg 1.000000e+04 train accuracy: 0.372102 val accuracy: 0.376000\n",
      "lr 1.000000e-07 reg 2.000000e+04 train accuracy: 0.382918 val accuracy: 0.384000\n",
      "lr 1.000000e-07 reg 2.500000e+04 train accuracy: 0.383020 val accuracy: 0.403000\n",
      "lr 1.000000e-07 reg 3.000000e+04 train accuracy: 0.376306 val accuracy: 0.385000\n",
      "lr 3.000000e-07 reg 1.000000e+04 train accuracy: 0.382878 val accuracy: 0.377000\n",
      "lr 3.000000e-07 reg 2.000000e+04 train accuracy: 0.369327 val accuracy: 0.374000\n",
      "lr 3.000000e-07 reg 2.500000e+04 train accuracy: 0.366224 val accuracy: 0.380000\n",
      "lr 3.000000e-07 reg 3.000000e+04 train accuracy: 0.360408 val accuracy: 0.395000\n",
      "lr 5.000000e-07 reg 1.000000e+04 train accuracy: 0.369857 val accuracy: 0.377000\n",
      "lr 5.000000e-07 reg 2.000000e+04 train accuracy: 0.359735 val accuracy: 0.371000\n",
      "lr 5.000000e-07 reg 2.500000e+04 train accuracy: 0.354469 val accuracy: 0.355000\n",
      "lr 5.000000e-07 reg 3.000000e+04 train accuracy: 0.331367 val accuracy: 0.362000\n",
      "lr 9.000000e-07 reg 1.000000e+04 train accuracy: 0.332653 val accuracy: 0.359000\n",
      "lr 9.000000e-07 reg 2.000000e+04 train accuracy: 0.313327 val accuracy: 0.322000\n",
      "lr 9.000000e-07 reg 2.500000e+04 train accuracy: 0.279102 val accuracy: 0.287000\n",
      "lr 9.000000e-07 reg 3.000000e+04 train accuracy: 0.305184 val accuracy: 0.317000\n",
      "best validation accuracy achieved during cross-validation: 0.403000\n"
     ]
    }
   ],
   "source": [
    "# Use the validation set to tune hyperparameters (regularization strength and\n",
    "# learning rate). You should experiment with different ranges for the learning\n",
    "# rates and regularization strengths; if you are careful you should be able to\n",
    "# get a classification accuracy of about 0.39 on the validation set.\n",
    "\n",
    "# Note: you may see runtime/overflow warnings during hyper-parameter search. \n",
    "# This may be caused by extreme values, and is not a bug.\n",
    "\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (training_accuracy, validation_accuracy). The accuracy is simply the fraction\n",
    "# of data points that are correctly classified.\n",
    "results = {}\n",
    "best_val = -1   # The highest validation accuracy that we have seen so far.\n",
    "best_svm = None # The LinearSVM object that achieved the highest validation rate.\n",
    "\n",
    "################################################################################\n",
    "# TODO:                                                                        #\n",
    "# Write code that chooses the best hyperparameters by tuning on the validation #\n",
    "# set. For each combination of hyperparameters, train a linear SVM on the      #\n",
    "# training set, compute its accuracy on the training and validation sets, and  #\n",
    "# store these numbers in the results dictionary. In addition, store the best   #\n",
    "# validation accuracy in best_val and the LinearSVM object that achieves this  #\n",
    "# accuracy in best_svm.                                                        #\n",
    "#                                                                              #\n",
    "# Hint: You should use a small value for num_iters as you develop your         #\n",
    "# validation code so that the SVMs don't take much time to train; once you are #\n",
    "# confident that your validation code works, you should rerun the validation   #\n",
    "# code with a larger value for num_iters.                                      #\n",
    "################################################################################\n",
    "\n",
    "# Provided as a reference. You may or may not want to change these hyperparameters\n",
    "learning_rates = [1e-7, 3e-7,5e-7,9e-7]\n",
    "regularization_strengths = [2.5e4, 1e4,3e4,2e4]\n",
    "\n",
    "\n",
    "# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "#pass\n",
    "\n",
    "for learning_rate in learning_rates:\n",
    "    for regularization_strength in regularization_strengths:\n",
    "        svm = LinearSVM()\n",
    "        loss_hist = svm.train(X_train, y_train, learning_rate=learning_rate, reg=regularization_strength,\n",
    "                      num_iters=1500, verbose=True)\n",
    "        y_train_pred = svm.predict(X_train)\n",
    "        y_val_pred = svm.predict(X_val)\n",
    "        y_train_acc = np.mean(y_train_pred==y_train)\n",
    "        y_val_acc = np.mean(y_val_pred==y_val)\n",
    "        results[(learning_rate,regularization_strength)] = [y_train_acc, y_val_acc]\n",
    "        if y_val_acc > best_val:\n",
    "            best_val = y_val_acc\n",
    "            best_svm = svm\n",
    "\n",
    "# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    \n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr, reg)]\n",
    "    print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "                lr, reg, train_accuracy, val_accuracy))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the cross-validation results\n",
    "import math\n",
    "import pdb\n",
    "\n",
    "# pdb.set_trace()\n",
    "\n",
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.tight_layout(pad=3)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "test"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.371000\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the best svm on test set\n",
    "y_test_pred = best_svm.predict(X_test)\n",
    "test_accuracy = np.mean(y_test == y_test_pred)\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true,
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the learned weights for each class.\n",
    "# Depending on your choice of learning rate and regularization strength, these may\n",
    "# or may not be nice to look at.\n",
    "w = best_svm.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(32, 32, 3, 10)\n",
    "w_min, w_max = np.min(w), np.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "      \n",
    "    # Rescale the weights to be between 0 and 255\n",
    "    wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "    plt.imshow(wimg.astype('uint8'))\n",
    "    plt.axis('off')\n",
    "    plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline question 2**\n",
    "\n",
    "Describe what your visualized SVM weights look like, and offer a brief explanation for why they look they way that they do.\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ *fill this in*  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
